LEADER 01782nam 2200421 n 450 001 996392806603316 005 20200824121712.0 035 $a(CKB)4940000000113306 035 $a(EEBO)2240899929 035 $a(UnM)ocm99885132e 035 $a(UnM)99885132 035 $a(EXLCZ)994940000000113306 100 $a19951114d1697 uy 101 0 $aeng 135 $aurbn||||a|bb| 200 14$aThe case of the Company of Glass-sellers in London, and all others selling glasses or earthen wares, in any city, burrough, town-corporate, or market-town in England and Wales, in relation to the bill for suppressing of hawkers, pedlers, &c$b[electronic resource] $eHumbly offered to the consideration of both the honourable Houses of Parliament 210 $a[London $cs.n.$d1697?] 215 $a1 sheet ([1] p.) 300 $aImprint from Wing. 300 $aWith marginal notes. 300 $aReproduction of original in the British Library. 330 $aeebo-0018 606 $aPeddlers and peddling$zEngland$vEarly works to 1800 606 $aRogues and vagabonds$vEarly works to 1800 606 $aGlass trade$zEngland$vEarly works to 1800 606 $aPottery, English$zEngland$vEarly works to 1800 615 0$aPeddlers and peddling 615 0$aRogues and vagabonds 615 0$aGlass trade 615 0$aPottery, English 801 0$bCu-RivES 801 1$bCu-RivES 801 2$bCStRLIN 801 2$bCu-RivES 906 $aBOOK 912 $a996392806603316 996 $aThe case of the Company of Glass-sellers in London, and all others selling glasses or earthen wares, in any city, burrough, town-corporate, or market-town in England and Wales, in relation to the bill for suppressing of hawkers, pedlers, &c$92384091 997 $aUNISA LEADER 03478nam 22005655 450 001 9910574052003321 005 20251202162147.0 010 $a3-030-97319-0 024 7 $a10.1007/978-3-030-97319-3 035 $a(MiAaPQ)EBC7007392 035 $a(Au-PeEL)EBL7007392 035 $a(CKB)23114200100041 035 $aEBL7007392 035 $a(AU-PeEL)EBL7007392 035 $a(PPN)269148477 035 $a(BIP)84392719 035 $a(BIP)83059771 035 $a(DE-He213)978-3-030-97319-3 035 $a(EXLCZ)9923114200100041 100 $a20220531d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aArtificial Intelligence for Financial Markets $eThe Polymodel Approach /$fby Thomas Barrau, Raphael Douady 205 $a1st ed. 2022. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2022. 215 $a1 online resource (182 pages) 225 1 $aFinancial Mathematics and Fintech,$x2662-7175 300 $aDescription based upon print version of record. 311 08$aPrint version: Barrau, Thomas Artificial Intelligence for Financial Markets Cham : Springer International Publishing AG,c2022 9783030973186 327 $a1. Introduction -- 2. Polymodel Theory: An Overview -- 3. Estimation Method: the Linear Non-Linear Mixed Model -- 4. Predictions of Market Returns -- 5. Predictions of Industry Returns -- 6. Predictions of Specific Returns -- 7. Genetic Algorithm-Based Combination of Predictions -- 8. Conclusions -- 9. Appendix. 330 $aThis book introduces the novel artificial intelligence technique of polymodels and applies it to the prediction of stock returns. The idea of polymodels is to describe a system by its sensitivities to an environment, and to monitor it, imitating what a natural brain does spontaneously. In practice this involves running a collection of non-linear univariate models. This very powerful standalone technique has several advantages over traditional multivariate regressions. With its easy to interpret results, this method provides an ideal preliminary step towards the traditional neural network approach. The first two chapters compare the technique with other regression alternatives and introduces an estimation method which regularizes a polynomial regression using cross-validation. The rest of the book applies these ideas to financial markets. Certain equity return components are predicted using polymodels in very different ways, and a genetic algorithm is describedwhich combines these different predictions into a single portfolio, aiming to optimize the portfolio returns net of transaction costs. Addressed to investors at all levels of experience this book will also be of interest to both seasoned and non-seasoned statisticians. 410 0$aFinancial Mathematics and Fintech,$x2662-7175 606 $aSocial sciences$xMathematics 606 $aMathematics in Business, Economics and Finance 615 0$aSocial sciences$xMathematics. 615 14$aMathematics in Business, Economics and Finance. 676 $a332.64028563 676 $a332.6015195 700 $aBarrau$b Thomas$01237779 702 $aDouady$b Raphae?l 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910574052003321 996 $aArtificial Intelligence for Financial Markets$92873125 997 $aUNINA